Reservoir surveillance, as part of the reservoir management process, involves the continuous monitoring of production data across a spectrum of possible levels of investigation, ranging from full field to individual well. It entails the collection, integration and comprehensive analysis of geologic and engineering reservoir and well performance data to maximize economic recovery and optimize the rate of recovery at both the well and reservoir level.
To effectively monitor and manage production, data should be available real-time, with tools available to investigate the data at various time increments (hours, days, months, etc.). Effective surveillance includes the ability to compare actual vs. predicted production (performance forecast) and adjust the prediction through history matching or other methods to derive production forecasts. In addition, it is also useful to compare and contrast multiple data types at multiple time steps and at multiple levels of investigation. Using current technology, this is typically done with static charts, plots and maps. Only limited capabilities are available to spatially represent geologic and engineering production data in 3D space. Nor is there capability to interact with the 2D plots to animate the temporal component of the production data. This is particularly problematic for large fields, with many wells and a long production life. As a result, identifying anomalous well and reservoir performance is time and labor intensive.
Current reservoir surveillance practice entails plotting and analyzing various field and well performance indicators through a series of 2D plots, such as those generated in Excel. Data are imported and manipulated in spreadsheets and static 2D plots are generated to analyze performance. Although all of the data may be available to do an analysis, identifying root causes of production problems usually requires significant manipulation and parsing of the data and comparing multiple static plots.
The current practice of reservoir surveillance most often is done at separate scales during the life cycle of the field's production history. Integration of scales is difficult and for each scale analyzed, the geoscientist or engineer typically uses a different set of data for the analysis. Hence, the impact of issues that are identified at one scale may not be readily identified at other scales.
The reservoir simulation model data would be useful to include in the analysis, but often, the well based model data and especially the cell based model data can not be easily integrated into the analysis. Geologic model data, such as horizons, faults and other geologic data from the field are used sparsely if not ignored entirely.
Finally, dynamic representation of the 3D spatial component of the production data is not possible. Nor is the ability to animate the production data through time concurrently in 3D space and in 2D plots.
More details on current reservoir surveillance methods can be found in references such as:    Al-Asimi et al. “Advances in Well and Reservoir Surveillance,” Oilfield Review, 14-35 (Winter 2002/2003);    O'Conner and Sherman, “Real-Time Reservoir Management—A New Paradigm for Enhanced Productivity,” Landmark Technical Review, Offshore, 32-35 (September 2002);    de Jonge et al. “Automated Reservoir Surveillance Through Data Mining Software,” Society of Petroleum Engineers, SPE 83974 (September 2003);    de Jonge and Stundner, “How Routine Reservoir Surveillance with Neural Networks and Simplified Reservoir Models can Convert Data into Information”, Society of Petroleum Engineers, SPE 78334, (October 2002);    Z. Tavassoli et al. “Errors in History Matching,” SPE Journal, 352-361 (September 2004);    Mattax and Dalton, “Reservoir Simulation,” SPE Monograph #13, Richardson Texas: Society of Petroleum Engineers, Chapter 18—“History Matching” (1990); and    Yamada, “Non-uniqueness of history matching,” Proc.—SPE Asia Pacific Conference (2000).
What is needed is a method for history updating of a simulation model that looks back to more fundamental models used to develop the simulator. The present method satisfies this need.